The communication of information is a necessity of modern society, which is enabled through the operation of a communication system. Information is communicated between a sending station and a receiving station by way of a communication channel. The sending station, if necessary, converts the information into a form for communication over the communication channel. The receiving station detects and recovers the information for the benefit of a user. A wide variety of different types of communication systems have been developed and are regularly employed to effectuate communication between sending and receiving stations.
An exemplary communication system is a cellular communication system in which a communication channel is defined upon a radio link extending between sending and receiving stations. Cellular radio communication systems are amenable to implementation as mobile communication systems wherein radio links, rather than fixed, wireline connections, are employed to define communication channels.
Generally, a cellular communication system includes a network infrastructure that includes a plurality of base stations that are positioned at spaced-apart locations throughout a geographic area. Each of the base stations defines an area, referred to as a cell, from which the cellular communication system derives its name. The network infrastructure, of which the base stations form portions thereof, is coupled to a core network such as a packet data backbone or a public-switched telephone network. Communication devices such as computer servers, telephone stations, etc., are, in turn, coupled to the core network and are capable of communication by way of the network infrastructure and the core network. Portable transceivers, commonly referred to as mobile stations, communicate with the base stations by way of such radio links.
Information communicated over a radio link is susceptible to imperfect communication such as distortion resulting from nonideal communication conditions. Distortion causes the information delivered to a receiving station to differ from the corresponding information transmitted by the sending station. If the distortion is significant, the informational content cannot be accurately recovered at the receiving station. For instance, fading caused by multi-path transmission distorts information communicated over a communication channel. If the communication channel exhibits significant levels of fading, the informational content may not be recoverable.
Various techniques such as spatial diversity are employed to compensate for or otherwise overcome distortion introduced upon the information transmitted over a communication channel to a receiving station. Spatial diversity is typically created through the use at a sending station of more than one transmit antenna from which information is transmitted, thereby creating spatial redundancy therefrom. The antennas are typically separated by distances sufficient to ensure that the information communicated by respective antennas fades in a sufficiently uncorrelated manner. Additionally, a receiving station can sometimes use more than one receiving antenna, preferably separated by appropriate distances.
Communication systems that utilize both multiple transmitting antennas and multiple receiving antennas are often referred to as being multiple-input, multiple-output (“MIMO”) systems. Communications in a MIMO system provide the possibility that higher overall communication performance of the system, relative to a conventional system, can be achieved. As a result, an increased number of users may be serviced or more data throughput may be provided with improved reliability for each user. The advantages provided through the use of spatial diversity are further enhanced if the sending station is provided with information about the state or performance of the communication channel between the sending and receiving stations.
In multiple antenna systems, an approach to increase the strength of a desired signal at the receiver is to make use of transmit beamforming. By coherently combining the signal transmitted from multiple transmit antennas, the signal-to-noise ratio (“SNR”) at the receiver of a transceiver can be increased, which leads to significant performance gains. Moreover, this approach also provides communication benefits by exploiting transmit diversity. However, this usually requires knowledge of channel state information (“CSI”) at the transmitter of a transceiver, which implies a high level of signaling/feedback overhead. The amount of feedback can be reduced by applying antenna weighting factors at the transmitter, and updating the antenna weighting factors using only limited feedback from the receiver. The feedback signal can be generated by perturbing the antenna weighting factors and estimating the impact of the perturbation at the receiver (e.g., by estimating the received signal power). The influence of the perturbation is then reflected in the feedback signal. This approach (which is also referred to as “subspace tracking”) allows adaptive antenna weighting factor learning, and closely converges to the performance gains achieved by coherent received signal combining.
A sending station generally cannot measure channel characteristics of the communication channel directly, such as a channel correlation matrix representing a product of channel impulse response components for the multiple transmitting antennas. Thus, a receiving station typically measures the characteristics of the communication channel. In two-way communication systems, measurements made at a receiving station can be returned to the sending station to provide channel characteristics to the sending station. Communication systems that provide this type of information to multiple-antenna sending stations are referred to as closed-loop transmit diversity systems.
The feedback signal returned to the sending station (e.g., a base station) from the receiving station (e.g., a mobile station) is used to select or refine values of antenna weighting factors. The antenna weighting factors are values including amplitude and phase by which information signals coupled to individual antennas are weighted prior to their transmission over a communication channel to the mobile station. A goal is to weight the information signals applied to the antennas in amplitude and phase in a manner that best facilitates communication of the information to the receiving station. Estimation of the antenna weighting factors can be formulated as a transmission subspace tracking procedure. Several closed-loop transmit diversity procedures may be utilized.
A technique to improve reliability of communication between a sending station and a receiving station is to employ relay nodes (“RNs”), which may be fixed or mobile communication nodes that act as signaling relays to improve the reception of a weak or corrupted signal at a destination node. A relay node forwards a message from a source node (“SN”), which is a node that needs assistance from a relay node, to a destination node (“DN”), which is the node that finally receives the message that may be weak or otherwise corrupted. In general, the aforementioned communication devices (e.g., SN, DN, or RN) form wireless nodes.
In a system employing relay nodes, in a simple but illuminating example, the problem can be translated into coherently combining desired signals at the relay nodes. This is done by co-phasing the received signals with respect to the backward channel (e.g., the source-relay channel) and the forward channel (e.g., the relay-destination channel) as described by H. Bölcskei, et al., in the paper entitled “Capacity Scaling Laws in MIMO Relay Networks,” IEEE Trans. Wireless Comm., Vol. 5, No. 6, pp. 1433-1444, June 2006, which is incorporated herein by reference. However, implementation of such a system to adjust antenna weighting factors requires feedback of the full CSI of the forward channel from the destination node to the relay nodes, which is clearly inefficient.
Several weighted transmission methods for a plurality of antennas have been studied in the past. However, efforts in this area have focused mainly on centralized antenna arrays, without the use of intervening relay nodes. In the paper by B. C. Banister, et al., entitled “Feedback Assisted Stochastic Gradient Adaptation of Multiantenna Transmission,” IEEE Trans. Wireless Comm., Vol. 4, No. 3, pp. 1121-1135, May 2005, and in U.S. Pat. No. 6,952,455, entitled “Adaptive Antenna Method and Apparatus,” by Bannister, Oct. 4, 2005, which are incorporated herein by reference, an iterative algorithm using one-bit feedback was described that uses random vector perturbations to achieve desired beamforming gains. In the paper by B. Raghothaman, entitled “Deterministic Perturbation Gradient Approximation for Transmission Subspace Tracking in FDD-CDMA,” Proc. IEEE ICC-2003, Vol. 4, pp. 2450-2454, May 2003, and in U.S. Pat. No. 6,842,632, entitled “Apparatus, and Associated Method, for Facilitating Antenna Weight Selection Utilizing Deterministic Perturbation Gradient Approximation,” by B. Raghothaman and R. T. Derryberry, Jan. 11, 2005, which are incorporated herein by reference, a similar approach utilizes a deterministic set of perturbation vectors. Both approaches are based on an adaptive gradient search technique and assume centralized antenna arrays, where the transmission weights are modified in the source transceiver.
As described in the paper by H. Nguyen and B. Raghothaman, entitled “Quantized-Feedback Optimal Adaptive Beamforming for FDD systems,” Proc. IEEE ICC-2006, Vol. 9, pp. 4202-4207, June 2006, which is incorporated herein by reference, the adaption rate of antenna weighting factors can be influenced by changing the amount of feedback (i.e., the number of feedback bits). Recently, beamforming algorithms for distributed transmitters have been investigated as described by R. Mudumbai, et al., in the paper entitled “Distributed Transmit Beamforming Using Feedback Control,” Arxiv preprint cs.IT/0603072, 2006, which is incorporated herein by reference. In the aforementioned paper, a virtual antenna array of sensors coherently transmits a common message to a base station. It is shown that coherent transmission can be achieved asymptotically by random phase perturbations at distributed transmitters. However, a relay arrangement including a relay node was not considered. In the above reference, the pilot signals are transmitted from the same spatial location where updating of antenna weighting factors is applied.
Considering the limitations as described above, a system and method to control antenna weighting factors for beamforming with multiple antennas employed in a wireless communication system including at least one source node, at least one relay node, and at least one destination node is not presently available. Accordingly, what is needed in the art is a system that learns real or complex antenna weighting factors for at least a subset of relay node antennas, preferably using low-rate feedback, overcoming many of the aforementioned limitations. In accordance therewith, a beamforming arrangement for multiple antennas in a communication system employing at least one source node, at least one relay node, and at least one destination node, that generates antenna weighting factors for beamforming of multiple relay node antennas would provide improved reliability of communication in a communication system.